HedgeRows - Bavaria, 2019-2021

Hedgerows play an important role in maintaining biodiversity, carbon sequestration, soil stability and the ecological integrity of agricultural landscapes. In this dataset, hedgerows are mapped for the whole of Bavaria. Orthophotos with a spatial resolution of 20 cm, taken in the period from 2019 to 2021, were used in a deep learning approach. Hedgerow polygons of the Bavarian in-situ biotope mapping from 5 districts (Miltenberg, Hassberge, Dillingen a.d. Donau, Freyung-Grafenau, Weilheim-Schongau) as well as other manually digitized polygons were used for training and testing as input into a DeepLabV3 Convolutional Neural Network (CNN). The CNN has a Resnet50 backbone and was optimized with the Dice loss as a cost function. The generated hedgerow probability tiles were post-processed by merging and averaging the overlapping tile boundaries, shape simplification and filtering. For more details, see Huber Garcia et al. (2025). The dataset has been created within the project FPCUP (https://www.copernicus-user-uptake.eu/) in close cooperation with Bayerisches Landesamt für Umwelt (LfU).